The significance of carbon nanotubes on styrene butadiene rubber (SBR) and SBR modified mortar

A New approach is introduced to incorporate multi-walled carbon nanotubes (MWCNTs) in cementitious materials. The MWCNTs are dispersed in styrene butadiene rubber (SBR) matrix before mixing the matrix with cement. Surfactants have been successfully applied to enhance the dispersion and functionalization of MWCNTs in SBR. The significance of using this MWCNTs–SBR nanocomposite on the mechanical characteristics including compressive and tensile strengths and microstructural features of latex modified mortar (LMM) were examined. Subsequently, the significance of the functionalized MWCNTs on surface chemistry, microstructure and thermal stability of SBR were characterized. MWCNTs were found to be a useful additive for enhancing the mechanical response and thermal stability of SBR. MWCNTs–SBR nanocomposite was observed to be able to bridge micro-cracks in the LMM which helped enhancing its mechanical properties. The ability of MWCNTs to enhance the mechanical response of SBR polymer matrix might be attributed to chemical bond that functionalized MWCNTs can establish with the SBR polymer matrix. The enhanced MWCNTs–SBR nanocomposite gave rise to improved microstructural features of the LMM. Microstructural investigations showed MWCNTs were well dispersed in and bonded to the SBR matrix.     

An evaluation of process-parameter and part-geometry effects on the quality of filling in micro-injection moulding

This paper addresses the use of micro-injection moulding for the fabrication of polymeric parts with microfeatures. Five separate parts with different micro-feature designs are moulded of Polymethylmethacrylate. The design-of-experiments approach is applied to correlate the quality of the parts to the processing parameters. Five processing parameters are investigated using a screening half-factorial experimentation plan to determine their possible effect on the filling quality of the moulded parts. The part mass is used as an output parameter to reflect the filling of the parts. The experiments showed that the holding pressure is the most significant processing parameter for all the different shapes. In addition, the experiments showed that the geometry of the parts plays a role in determining the significant processing parameters. For a more complex part, injection speed and mould temperature became statistically significant. A desirability function approach was successfully used to improve the filling quality of each part.     

Customer Prioritization for Medical Supply Chain During COVID-19 Pandemic

During COVID-19, the escalated demand for various pharmaceutical products with the existing production capacity of pharmaceutical companies has stirred the need to prioritize its customers in order to fulfill their demand. This study considers a two-echelon pharmaceutical supply chain considering various pharma-distributors as its suppliers and hospitals, pharmacies, and retail stores as its customers. Previous studies have generally considered a balanced situation in terms of supply and demand whereas this study considers a special situation of COVID-19 pandemic where demand exceeds supply Various criteria have been identified from the literature that influences the selection of customers. A questionnaire has been developed to collect primary data from pharmaceutical suppliers pertaining to customer-selection criteria. These criteria have been prioritized with respect to eigenvalues obtained from Principal Component Analysis and also validated with the experts’ domain-related knowledge using Analytical Hierarchy Process. Profit potential appeared to be the most important criteria of customer selection followed by trust and service convenience brand loyalty, commitment, brand awareness, brand image, sustainable behavior, and risk. Subsequently, Multi Criteria Decision Analysis has been performed to prioritize the customer-selection criteria and customers with respect to selection criteria. Three experts with seven and three and ten years of experience have participated in the study. Findings of the study suggest large hospitals, large pharmacies, and small retail stores are the highly preferred customers. Moreover, findings of prioritization of customer-selection criteria from both Principal Component Analysis and Analytical Hierarchy Process are consistent. Furthermore, this study considers the experience of three experts to calculate an aggregate score of priorities to reach an effective decision. Unlike traditional supply chain problems of supplier selection, this study considers a selection of customers and is useful for procurement and supply chain managers to prioritize customers while considering multiple selection criteria.     

Optimal Parameter Estimation of Transmission Line Using Chaotic Initialized Time-Varying PSO Algorithm

Transmission line is a vital part of the power system that connects two major points, the generation, and the distribution. For an efficient design, stable control, and steady operation of the power system, adequate knowledge of the transmission line parameters resistance, inductance, capacitance, and conductance is of great importance. These parameters are essential for transmission network expansion planning in which a new parallel line is needed to be installed due to increased load demand or the overhead line is replaced with an underground cable. This paper presents a method to optimally estimate the parameters using the input-output quantities i.e., voltages, currents, and power factor of the transmission line. The equivalent π-network model is used and the terminal data i.e., sending-end and receiving-end quantities are assumed as available measured data. The parameter estimation problem is converted to an optimization problem by formulating an error-minimizing objective function. An improved particle swarm optimization (PSO) in terms of time-varying control parameters and chaos-based initialization is used to optimally estimate the line parameters. Two cases are considered for parameter estimation, the first case is when the line conductance is neglected and in the second case, the conductance is considered into account. The results obtained by the improved algorithm are compared with the standard version of the algorithm, firefly algorithm and artificial bee colony algorithm for 30 number of trials. It is concluded that the improved algorithm is tremendously sufficient in estimating the line parameters in both cases validated by low error values and statistical analysis, comparatively.     

A Vicenary Analysis of SARS-CoV-2 Genomes

Coronaviruses are responsible for various diseases ranging from the common cold to severe infections like the Middle East syndromes and the severe acute respiratory syndrome. However, a new coronavirus strain known as COVID-19 developed into a pandemic resulting in an ongoing global public health crisis. Therefore, there is a need to understand the genomic transformations that occur within this family of viruses in order to limit disease spread and develop new therapeutic targets. The nucleotide sequences of SARS-CoV-2 are consist of several bases. These bases can be classified into purines and pyrimidines according to their chemical composition. Purines include adenine (A) and guanine (G), while pyrimidines include cytosine (C) and tyrosine (T). There is a need to understand the spatial distribution of these bases on the nucleotide sequence to facilitate the development of antivirals (including neutralizing antibodies) and epitomes necessary for vaccine development. This study aimed to evaluate all the purine and pyrimidine associations within the SARS-CoV-2 genome sequence by measuring mathematical parameters including; Shannon entropy, Hurst exponent, and the nucleotide guanine-cytosine content. The Shannon entropy is used to identify closely associated sequences. Whereas Hurst exponent is used to identifying the auto-correlation of purine-pyrimidine bases even if their organization differs. Different frequency patterns can be used to determine the distribution of all four proteins and the density of each base. The GC-content is used to understand the stability of the DNA. The relevant genome sequences were extracted from the National Center for Biotechnology Information (NCBI) virus database. Furthermore, the phylogenetic properties of the COVID-19 virus were characterized to compare the closeness of the COVID-19 virus with other coronaviruses by evaluating the purine and pyrimidine distribution.     

Durable and Recyclable Superhydrophobic Fabric and Mesh for Oil–Water Separation

The authors report durable and recyclable nanocomposite superhydrophobic coatings on two different substrates of fabric and mesh as prepared by titania nanoparticles and polydimethysiloxane (PDMS). The felted wool fabric and the steel mesh are initially coated with a thin layer of PDMS, which is followed by the deposition of nanocomposite coating of titania nanoparticles embedded in PDMS. The dual surface modification of two kinds of substrates generates highly hydrophobic surface character, which is retained after durability performance as measured in ultrasonication, sand, and emery paper abrasion tests. Oil–water separation experiments are performed using water mixtures with four oils, that is, n‐hexane, toluene, kerosene, and diesel to ensure the industrial applications of prepared composite materials. Moreover, nanocomposite coatings are tested for several cycles of oil–water separation in harsh conditions such as hot water, sodium chloride, and hydrochloric acid. The adopted approach improves the separation performance by inducing durability of the prepared nanocomposite coatings along with introducing recyclable character.     

Interfacial Behavior and Debonding Failures in FRP-Strengthened Concrete Slabs

It has been demonstrated, through laboratory investigations and various field projects, that the external bonding of fiber- reinforced polymer (FRP) laminates is an effective technique for the structural enhancement of reinforced concrete slabs. In such applications, failure is generally governed by debonding of the FRP laminate. Nevertheless, numerical simulations to date of FRP-strengthened slabs have usually been based on the assumption of full bond between the concrete and FRP. In this study, the interfacial behavior between the FRP laminates and the concrete substrate is accounted for by introducing appropriate bond-slip models for the interface in a nonlinear finite-element analysis of FRP-strengthened two-way slabs. The numerical model is capable of simulating slabs strengthened in shear or in flexure; it can be applied to arbitrary FRP configurations, and can also accommodate both passive as well as prestressed FRP strengthening schemes. Results are presented in terms of load-deflection relationships, ultimate load capacities, failure modes, and interfacial slip and stress distributions. When compared to test results reported in the literature, the analysis is shown to lead to excellent predictions in that, for the entire set of FRP-strengthened specimens considered, the average of the numerical-to-experimental load capacity ratios is 0.966, with a standard deviation of 0.066. Furthermore, in all cases when FRP debonding was observed experimentally, the analysis correctly predicted the mode of failure.     

Dietary mycotoxins binders: a strategy to reduce aflatoxin m1 residues and improve milk quality of lactating Beetal goats

Aflatoxin M1 (AFM1) is a metabolite of aflatoxin B1 (AFB1) and secreted in milk of animals that are kept on a moldy diet. AFB1 is produced by several toxigenic species of fungi. In this study, the comparative efficacy of two mycotoxin binders was evaluated in terms of reducing excretion of AFM1, total viable bacterial count and somatic cell count in milk obtained from goats fed with AFB1 contaminated diet. A total of 32 lactating Beetal goats were reared and divided into 4 equal groups: Animals of group A were kept as control, while those in groups B, C, and D were individually fed with AFB1 at 40 µg alone, 40 µg AFB1 along with mycotoxin binder Toxfin^® at 3 g kg^?1 of cotton seed cake, and 40 µg AFB1 along with mycotoxin binder Elitox^® at a dose rate of 1 g kg^?1 of cotton seed cake, respectively. Toxfin^® significantly decreased the excretion of AFM1 in goats’ milk by 49.57 % while Elitox^® non-significantly reduced the excretion of AFM1 in goats’ milk by 19.49 %. Total viable bacterial count in milk samples of group C and D, and somatic cell count in milk samples of group C did not reduce significantly. However, somatic cell count in milk samples of group D reduced significantly. We conclude that the addition of Toxfin^® in the moldy diet significantly reduce the excretion of AFM1 in animals’ milk and minimize the risk of mycotoxin toxicity to public health.